Estimation of unknown parameters and functions involved in complex nonlinear econometric models is a very important issue. Existing estimation methods include generalised method of moments (GMM) by Hansen (1982) and others, efficient method of moments (EMM) by Gallant and Tauchen (1997), Markov chain Monte Carlo (MCMC) method by Chernozhukov and Hong (2003), and nonparametric simulated maximum ...

Variational (deep) parametric auto-encoders (VAE) have shown a great potential for unsupervised extraction of latent representations from large amounts of data. Human face exhibits an inherent hierarchy in facial representations (encoded in facial action units (AUs) and their intensity). This makes VAE a sophisticated method for learning facial features for AU intensity estimation. Yet, most ex...

Recently, quantile regression (QR) models are often applied for longitudinal data analysis. When the distribution of responses seems to be skew and asymmetric due to outliers and heavy-tails, QR models may work suitably. In this paper, a semi-parametric quantile regression model is developed for analysing continuous longitudinal responses. The error term's distribution is assumed to be Asymmetr...

Modelling Lorenz curves (LC) for stochastic dominance comparisons is central to the analysis of income distribution. It is conventional to use non-parametric statistics based on empirical income cumulants which are in the construction of LC and other related second-order dominance criteria. However, although attractive because of its simplicity and its apparent flexibility, this approach suffer...

In this paper we summarize analysis of galaxy spectra from the Sloan Digital Sky Survey. To each spectrum we fit non–parametrically a continuum, that is a smooth underlying trend, and a parametric “island” of spike profiles at each group (opportunely defined) of adjacent absorption or emission line locations, having, as ultimate inferential goal, the construction of reliable confidence interval...

In the mid-1980s, many European countries introduced ...xed-term contracts. This paper studies the possible implications of such reforms for the duration distribution of unemployment. I estimate a parametric duration model using cross-sectional data drawn from the Spanish Labor Force Survey from 1980 to 1994 to analyze the probability of leaving unemployment before and after the introduction of...

Recent advances in the econometric modelling of count data have often been based on the generalized method of moments (GMM). However, the two-step GMM procedure may perform poorly in small samples, and several empirical likelihood-based estimators have been suggested alternatively. In this paper I discuss empirical likelihood (EL) estimation for count data models with endogenous regressors. I c...

This paper reports on work which fuses three different appearance models to enable robust tracking of multiple objects on the basis of colour. Short-term variation in object colour is modelled non-parametrically using adaptive binning histograms. Appearance changes at intermediate time scales are represented by semi-parametric (Gaussian mixture) models while a parametric subspace method (Robust...